Fundamental Green Tradeoffs: Progresses, Challenges, and Impacts on 5G Networks

By Shunqing Zhang, Qingqing Wu, Shugong Xu, Geoffrey Y. Li. IEEE Communications Surveys and Tutorials, 2016

318 citations recorded by the source corpus.

With years of tremendous traffic and energy consumption growth, green radio has been valued not only for theoretical research interests but also for the operational expenditure reduction and the sustainable development of wireless communications. Fundamental green tradeoffs, served as an important framework for analysis, include four basic relationships: 1) spectrum efficiency versus energy efficiency; 2) deployment efficiency versus energy efficiency; 3) delay versus power; and 4) bandwidth versus power. In this paper, we first provide a comprehensive overview on the extensive on-going research efforts and categorize them based on the fundamental green tradeoffs. We will then focus on research progresses of 4G and 5G communications, such as orthogonal frequency division multiplexing and non-orthogonal aggregation, multiple input multiple output, and heterogeneous networks. We will also discuss potential challenges and impacts of fundamental green tradeoffs, to shed some light on the energy efficient research and design for future wireless networks.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/83d5b8873277e2935e0c0c95170fc19c9410d2c3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Accessing From the Sky: A Tutorial on UAV Communications for 5G and Beyond (2019, background): “…Q ( t ) = { q k ( t ) } Kk =1 , 0 ≤ t ≤ T , the average communication throughput of UAV k can be written as 4) Energy Efﬁciency: Energy efﬁciency is measured by the number of information bits that can be reliably communicated per unit energy consumed, thus measured in bits/Joule [18, 77]–[79].”
Common Throughput Maximization in UAV-Enabled OFDMA Systems With Delay Consideration (2018, background): “Future wireless networks are expected to provide different quality-of-service (QoS) guarantees for a wide range of applications with diversified requirements [22], [23].”
Beamforming Optimization for Wireless Network Aided by Intelligent Reflecting Surface With Discrete Phase Shifts (2019, background): “2958916 and high hardware cost are still the main hindrances to its implementation in practice [2]–[5].”
Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey (2019, background): “…(IoT), we have never stopped our efforts on the challenging network optimization problems to improve the energy-or spectrum-efﬁciency (EE/SE) of wireless networks, with the aim of accommodating the users’ demanding data rate and diverse quality of service (QoS) requirements, e.g., [1] and [2].”
Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network (2019, background): “ending massive MIMO from sub-6 GHz to mmWave frequency bands generally requires more complex signal processing as well as more costly and energy consuming hardware (e.g., radio frequency (RF) chains) [3]. Therefore, research on ﬁnding innovative, spectral and energy efﬁcient, and yet cost-effective ”
Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming (2018, background): “However, the network energy consumption and hardware cost still remain critical issues in practical systems [3].”
Intelligent Reflecting Surface Enhanced Wireless Networks: Two-Timescale Beamforming Optimization (2019, background): “However, equipping a large number of antennas may lead to more circuit energy consumption and higher hardware cost, especially as the wireless system evolves into the new era of millimeter-wave (mmWave) communications [3].”
Intelligent Reflecting Surface Enhanced Wireless Network: Joint Active and Passive Beamforming Design (2018, background): “Although there has been a quantum leap in spectrum efficiency of wireless networks in the last few decades thanks to various technological advances such as ultra-dense network (UDN), massive multiple-input multiple-output (M-MIMO), and millimeter wave (mmWave) communications, the network energy cons”
A Comprehensive Overview on 5G-and-Beyond Networks With UAVs: From Communications to Sensing and Intelligence (2020, background): “…Generally speaking, the energy consumption challenge to achieve green and self-sustainable MTC networks could be addressed by a proper combination of energy harvesting and/or energy-efﬁcient designs which has drawn signiﬁcant interest from both academia and industry [73], [74], [150], [188]–[190].”
Securing UAV Communications via Joint Trajectory and Power Control (2018, background): “in wireless communication [2], and are expected to play a significant role in the forthcoming fifth-generation (5G) wireless networks [3], [4].”
Weighted Sum Power Maximization for Intelligent Reflecting Surface Aided SWIPT (2019, background): “In particular, an asymptotic squared signal-to-noise ratio (SNR) gain is derived in [5], which is larger than the linear beamforming gain in both massive MIMO and MIMO relay systems [5], [7].”